LEARNING BRAIN
LEARNING BRAIN - a longitudinal dataset on neural plasticity dynamics in Braille and music training
Repeated brain MRI and task fMRI of healthy young women learning tactile Braille reading or piano playing, with an untrained control group, collected to follow the time course of learning-related brain plasticity over six to seven sessions. Images are preprocessed in MNI space.
Overview
LEARNING BRAIN follows how the brains of young adults change while they learn a new skill. Healthy young women were assigned to a tactile Braille reading course, a piano course, or a control group without any training, and were scanned repeatedly from one week before training, through several months of training, to a follow-up two to three months after it ended. The study ran from September 2020 to July 2022. The OpenNeuro release shares preprocessed images, task events and behavioural test results in BIDS layout.
Composition
There are 60 participants: 17 in the Braille group, 24 in the music group and 19 controls. According to participants.tsv all are female and right-handed, aged 18 to 24 at the first session. Sessions are labelled pre, 0, 1, 2, 3, 4 and 5 (one week before training, training onset, after one, six and 13 weeks, end of training, follow-up). The file tree holds 401 sessions with fMRI: 41 participants have seven and 19 have six. Each participant has one T1-weighted image averaged across sessions, with grey matter, white matter and CSF probability maps, a discrete tissue segmentation and a brain mask. The 1,502 BOLD runs cover resting state, finger tapping, passive music listening, a six-dot detection task and a Braille lexical decision task on an MRI-compatible Braille display, and a piano playback task on an MRI-compatible keyboard. Which tasks a person did depends on the group and session. Outside the scanner, n-back and Stroop tests were run at three time points.
Acquisition
All scans come from a Siemens TrioTim 3 T scanner with a 32-channel head coil at the Institute of Experimental Biology in Warsaw. The BOLD runs use a multiband (factor 3) echo-planar sequence with a repetition time of 1.41 s and 2.5 mm slices; the two music tasks use interleaved silent steady-state acquisition so that sounds play in silent gaps. The T1-weighted scans are 1 mm MP-RAGE. All images were preprocessed with fMRIPrep and resampled to MNI152NLin2009cAsym space; confound tables come with every run.
Known limitations
Raw scanner images are not shared, only the normalised fMRIPrep outputs. The cohort is small, female only and narrow in age. Group sizes differ and task coverage varies by group and session. The root dataset_description.json states CC0, while the fMRIPrep derivative folder, which holds all images, states CC BY 4.0.
Cohort
Aggregate numbers from the sources below. Bars are relative to the 60 subjects.
Contrast / sequence
Groups can overlap
- T1-weighted 60 100%
- BOLD fMRI 60 100%
Scanner vendor
- Siemens Healthineers 60 100%
Age
mean 21.1, median 21, range 18 to 24
Condition
Groups can overlap
- Healthy control 60 100%
README.md in OpenNeuro ds007022 snapshot 1.1.0 (dataset_description.json, README.md and CHANGES)
Field strength
- 3 T 60 100%
MagneticFieldStrength in Derivative file tree of ds007022 (derivatives/fMRIPrep, CC BY 4.0), preprocessed T1w and BOLD NIfTI files counted per subject, session and task, scanner fields read from the JSON sidecars
Contrast combinations
How many subjects have exactly each set of contrasts.
| T1w | bold | Subjects with exactly this set |
|---|---|---|
60 |
License and access
Our reading of the license, not legal advice. Before you use the data, read the original license and confirm that your use is allowed. We take no responsibility for how you use a dataset. Full disclaimer
Download without an account
Different parts of the data carry different licenses. The summary on the right shows the most restrictive answer per rule.
Creative Commons Zero 1.0 Universal
Public domain dedication. Do anything with the data, including commercial use, without asking and without having to give credit.
dataset_description.json at the dataset root of snapshot 1.1.0 states "License" CC0.
What you can do
- Yes
- Yes
- Yes
- Yes
- Yes
What you can share
- Yes
- Yes
- Yes
What you must do
- No
- Share alike No
- No
- No
- Manuscript review No
- Release code No
- Return results No
- Delete after use No
Limits
- No
- Location limits No
Creative Commons Attribution 4.0 International
Use, share and adapt the data for any purpose, including commercial use, as long as you credit the creators.
derivatives/fMRIPrep/dataset_description.json states "License" CC BY 4.0.
What you can do
- Yes
- Yes
- Yes
- Yes
- Yes
What you can share
- Yes
- Yes
- Yes
What you must do
- Yes
- Share alike No
- No
- No
- Manuscript review No
- Release code No
- Return results No
- Delete after use No
Limits
- No
- Location limits No
Citation
Olszewska AM, Gaca M, Droździel D, Kossowski B, Herman AM, Marchewka A. LEARNING BRAIN - a longitudinal dataset on neural plasticity dynamics in Braille and music training. OpenNeuro (2025). doi:10.18112/openneuro.ds007022.v1.1.0
Sources
Every number on this page comes from one of these documents. Each chart names the table or page it is taken from. The raw numbers are in stats.csv.
- OpenNeuro ds007022 snapshot 1.1.0 (dataset_description.json, README.md and CHANGES) website
- participants.tsv of ds007022 (CC0), counted per row computed
- Derivative file tree of ds007022 (derivatives/fMRIPrep, CC BY 4.0), preprocessed T1w and BOLD NIfTI files counted per subject, session and task, scanner fields read from the JSON sidecars computed